Prediction of Liquid Slosh Damping Using a High Resolution CFD Tool

Propellant slosh is a potential source of disturbance critical to the stability of space vehicles. The slosh dynamics are typically represented by a mechanical model of a spring mass damper. This mechanical model is then included in the equation of motion of the entire vehicle for Guidance, Navigation and Control analysis. Our previous effort has demonstrated the soundness of a CFD approach in modeling the detailed fluid dynamics of tank slosh and the excellent accuracy in extracting mechanical properties (slosh natural frequency, slosh mass, and slosh mass center coordinates). For a practical partially-filled smooth wall propellant tank with a diameter of 1 meter, the damping ratio is as low as 0.0005 (or 0.05%). To accurately predict this very low damping value is a challenge for any CFD tool, as one must resolve a thin boundary layer near the wall and must minimize numerical damping. This work extends our previous effort to extract this challenging parameter from first principles: slosh damping for smooth wall and for ring baffle. First the experimental data correlated into the industry standard for smooth wall were used as the baseline validation. It is demonstrated that with proper grid resolution, CFD can indeed accurately predict low damping values from smooth walls for different tank sizes. The damping due to ring baffles at different depths from the free surface and for different sizes of tank was then simulated, and fairly good agreement with experimental correlation was observed. The study demonstrates that CFD technology can be applied to the design of future propellant tanks with complex configurations and with smooth walls or multiple baffles, where previous experimental data is not available

Multilingual Word Sense Induction to Improve Web Search Result Clustering

In [12] a novel approach to Web search result clustering based on Word Sense Induction, i.e. the automatic discovery of word senses from raw text was presented; key to the proposed approach is the idea of, first, automatically in- ducing senses for the target query and, second, clustering the search results based on their semantic similarity to the word senses induced. In [1] we proposed an innovative Word Sense Induction method based on multilingual data; key to our approach was the idea that a multilingual context representation, where the context of the words is expanded by considering its translations in different languages, may im- prove the WSI results; the experiments showed a clear per- formance gain. In this paper we give some preliminary ideas to exploit our multilingual Word Sense Induction method to Web search result clustering

Lujan-Fryns syndrome (mental retardation, X-linked, marfanoid habitus)

The Lujan-Fryns syndrome or X-linked mental retardation with marfanoid habitus syndrome is a syndromal X-linked form of mental retardation, affecting predominantly males. The prevalence is not known for the general population. The syndrome is associated with mild to moderate mental retardation, distinct facial dysmorphism (long narrow face, maxillary hypoplasia, small mandible and prominent forehead), tall marfanoid stature and long slender extremities, and behavioural problems. The genetic defect is not known. The diagnosis is based on the presence of the clinical manifestations. Genetic counselling is according to X-linked recessive inheritance. Prenatal testing is not possible. There is no specific treatment for this condition. Patients need special education and psychological follow-up, and attention should be given to diagnose early psychiatric disorders

Development of superlattice CrNNbN coatings for joint replacements deposited by High Power Impulse Magnetron Sputtering

The demand for reliable coating on medical implants is ever growing. In this research, enhanced performance of medical implants was achieved by a CrN/NbN coating utilising nanoscale multilayer/superlattice structure. The advantages of the novel High Power Impulse Magnetron Sputtering technology, namely its unique highly ionised plasma were exploited to deposit dense and strongly adherent coatings on Co-Cr implants. TEM analyses revealed coating superlattice structure with bi-layer thickness of 3.5 nm. CrN/NbN deposited on Co-Cr samples showed exceptionally high adhesion, critical load values of LC2= 50 N in scratch adhesion tests. Nanoindentation tests showed high hardness of 34 GPa and Young's modulus of 447 GPa. Low coefficient of friction (µ) 0.49 and coating wear coefficient (KC) = 4.94 x 10-16 m3N-1m-1 were recorded in dry sliding tests. Metal ion release studies showed a reduction in Co, Cr and Mo release at physiological and elevated temperatures, (70 oC) to almost undetectable levels (<1 ppb). Rotating beam fatigue testing showed a significant increase in fatigue strength from 349±59 MPa (uncoated) to 539±59 MPa (coated). In vitro biological testing has been performed in order to assess the safety of the coating in biological environment, cytotoxicity, genotoxicity and sensitisation testing have been performed, all showing no adverse effects. Keywords: Orthopaedic implant, High Power Impulse Magnetron Sputtering, Superlattice coating, Corrosion, Biocompatibility

Oxidative and pre-inflammatory stress in wedge resection of pulmonary parenchyma using the radiofrequency ablation technique in a swine model

<p>Abstract</p> <p>Background</p> <p>Radiofrequency ablation (RFA) is a thermal energy delivery system used for coagulative cellular destruction of small tumors through percutaneous or intraoperative application of its needle electrode to the target area, and for assisting partial resection of liver and kidney. We tried to evaluate the regional oxidative and pre-inflammatory stress of RFA-assisted wedge lung resection, by measuring the MDA and tumor Necrosis Factor Alpha (TNF-α) concentration in the resected lung tissue of a swine model.</p> <p>Method</p> <p>Fourteen white male swines, divided in two groups, the RFA-group and the control group (C-group) underwent a small left thoracotomy and wedge lung resection of the lingula. The wedge resection in the RFA-group was performed using the RFA technique whereas in C-group the simple "cut and sew" method was performed. We measured the malondialdehyde (MDA) and TNF-α concentration in the resected lung tissue of both groups.</p> <p>Results</p> <p>In C-group the MDA mean deviation rate was 113 ± 42.6 whereas in RFA-group the MDA mean deviation rate was significantly higher 353 ± 184 (p = 0.006). A statistically significant increase in TNF-α levels was also observed in the RFA-group (5.25 ± 1.36) compared to C-group (mean ± SD = 8.48 ± 2.82) (p = 0.006).</p> <p>Conclusion</p> <p>Our data indicate that RFA-assisted wedge lung resection in a swine model increases regional MDA and TNF-a factors affecting by this oxidative and pre-inflammatory stress of the procedure. Although RFA-assisted liver resection can be well tolerated in humans, the possible use of this method to the lung has to be further investigated in terms of regional and systemic reactions and the feasibility of performing larger lung resections.</p

Tackling increased risks in older adults with intellectual disability and epilepsy: data from a national multicentre cohort study

Purpose: People with intellectual disabilities (ID) suffer multimorbidity, polypharmacy and excess mortality at a younger age than general population. Those with ID and epilepsy are at higher risk of worse clinical outcomes than their peers without epilepsy. In the ID population the health profile of those aged ≥40 years can be compared to those aged over 65 in the general population. To date there is limited data available to identify clinical characteristics and risk factors in older adults (≥40 years) with ID and epilepsy. / Methods: The Epilepsy in ID National Audit (Epi-IDNA) identified 904 patients with ID and epilepsy from 10 sites in England and Wales. This subsequent analysis of the Epi-IDNA cohort compared the 405 adults over 40 years with 499 adults ≥18 years aged under 40 years. Comparison was made between clinical characteristics and established risk factors using the Sudden Unexpected Death in Epilepsy (SUDEP) and Seizure Safety Checklist. / Results: The older adults’ cohort had significantly higher levels of co-morbid physical health conditions, mental health conditions, anti-seizure medications (median 5), and antipsychotics compared to the younger cohort. The older group were significantly less likely to be diagnosed with a co-morbid neurodevelopmental disorder, and to have an epilepsy care plan. / Conclusion: This is the largest study to date focused on adults with ID and epilepsy over 40 years. The ≥40 years cohort compared to the younger group has higher levels of clinical risk factors associated with multi-morbidity, potential iatrogenic harm and premature mortality with worse clinical oversight mechanisms

Collocation analysis for UMLS knowledge-based word sense disambiguation

BACKGROUND: The effectiveness of knowledge-based word sense disambiguation (WSD) approaches depends in part on the information available in the reference knowledge resource. Off the shelf, these resources are not optimized for WSD and might lack terms to model the context properly. In addition, they might include noisy terms which contribute to false positives in the disambiguation results. METHODS: We analyzed some collocation types which could improve the performance of knowledge-based disambiguation methods. Collocations are obtained by extracting candidate collocations from MEDLINE and then assigning them to one of the senses of an ambiguous word. We performed this assignment either using semantic group profiles or a knowledge-based disambiguation method. In addition to collocations, we used second-order features from a previously implemented approach.Specifically, we measured the effect of these collocations in two knowledge-based WSD methods. The first method, AEC, uses the knowledge from the UMLS to collect examples from MEDLINE which are used to train a Naïve Bayes approach. The second method, MRD, builds a profile for each candidate sense based on the UMLS and compares the profile to the context of the ambiguous word.We have used two WSD test sets which contain disambiguation cases which are mapped to UMLS concepts. The first one, the NLM WSD set, was developed manually by several domain experts and contains words with high frequency occurrence in MEDLINE. The second one, the MSH WSD set, was developed automatically using the MeSH indexing in MEDLINE. It contains a larger set of words and covers a larger number of UMLS semantic types. RESULTS: The results indicate an improvement after the use of collocations, although the approaches have different performance depending on the data set. In the NLM WSD set, the improvement is larger for the MRD disambiguation method using second-order features. Assignment of collocations to a candidate sense based on UMLS semantic group profiles is more effective in the AEC method.In the MSH WSD set, the increment in performance is modest for all the methods. Collocations combined with the MRD disambiguation method have the best performance. The MRD disambiguation method and second-order features provide an insignificant change in performance. The AEC disambiguation method gives a modest improvement in performance. Assignment of collocations to a candidate sense based on knowledge-based methods has better performance. CONCLUSIONS: Collocations improve the performance of knowledge-based disambiguation methods, although results vary depending on the test set and method used. Generally, the AEC method is sensitive to query drift. Using AEC, just a few selected terms provide a large improvement in disambiguation performance. The MRD method handles noisy terms better but requires a larger set of terms to improve performance

A Requirement for Zic2 in the Regulation of Nodal Expression Underlies the Establishment of Left-Sided Identity

ZIC2 mutation is known to cause holoprosencephaly (HPE). A subset of ZIC2 HPE probands harbour cardiovascular and visceral anomalies suggestive of laterality defects. 3D-imaging of novel mouse Zic2 mutants uncovers, in addition to HPE, laterality defects in lungs, heart, vasculature and viscera. A strong bias towards right isomerism indicates a failure to establish left identity in the lateral plate mesoderm (LPM), a phenotype that cannot be explained simply by the defective ciliogenesis previously noted in Zic2 mutants. Gene expression analysis showed that the left-determining NODAL-dependent signalling cascade fails to be activated in the LPM, and that the expression of Nodal at the node, which normally triggers this event, is itself defective in these embryos. Analysis of ChiP-seq data, in vitro transcriptional assays and mutagenesis reveals a requirement for a low-affinity ZIC2 binding site for the activation of the Nodal enhancer HBE, which is normally active in node precursor cells. These data show that ZIC2 is required for correct Nodal expression at the node and suggest a model in which ZIC2 acts at different levels to establish LR asymmetry, promoting both the production of the signal that induces left side identity and the morphogenesis of the cilia that bias its distribution

Mass spectrometry and multivariate analysis to classify cervical intraepithelial neoplasia from blood plasma: an untargeted lipidomic study

Cervical cancer is still an important issue of public health since it is the fourth most frequent type of cancer in women worldwide. Much effort has been dedicated to combating this cancer, in particular by the early detection of cervical pre-cancerous lesions. For this purpose, this paper reports the use of mass spectrometry coupled with multivariate analysis as an untargeted lipidomic approach to classifying 76 blood plasma samples into negative for intraepithelial lesion or malignancy (NILM, n = 42) and squamous intraepithelial lesion (SIL, n = 34). The crude lipid extract was directly analyzed with mass spectrometry for untargeted lipidomics, followed by multivariate analysis based on the principal component analysis (PCA) and genetic algorithm (GA) with support vector machines (SVM), linear (LDA) and quadratic (QDA) discriminant analysis. PCA-SVM models outperformed LDA and QDA results, achieving sensitivity and specificity values of 80.0% and 83.3%, respectively. Five types of lipids contributing to the distinction between NILM and SIL classes were identified, including prostaglandins, phospholipids, and sphingolipids for the former condition and Tetranor-PGFM and hydroperoxide lipid for the latter. These findings highlight the potentiality of using mass spectrometry associated with chemometrics to discriminate between healthy women and those suffering from cervical pre-cancerous lesions